U.S. patent application number 10/747282 was filed with the patent office on 2005-07-07 for analysis method about relationship of beating signal and heart function.
Invention is credited to Huang, Liang-Hsiung, Huang, Shih-Fang.
Application Number | 20050148888 10/747282 |
Document ID | / |
Family ID | 34710782 |
Filed Date | 2005-07-07 |
United States Patent
Application |
20050148888 |
Kind Code |
A1 |
Huang, Liang-Hsiung ; et
al. |
July 7, 2005 |
Analysis method about relationship of beating signal and heart
function
Abstract
This is one analysis method about probing into relationship of
beating signal and heart function. It is used to deal with one
beating signal, which is measured from one subject under any
activity condition in a period of time with an electric manometer.
And this analysis could be the reference target of the heart
function of the subject. This method includes: (1) to transform the
beating signal into the power spectrum, (2) to normalize the
outcome of the power spectrum transformation, and (3) to compute an
advance defining heart index from the normalized power spectrum
diagram, and supply the reference target of the heart function from
the subject with the heart index.
Inventors: |
Huang, Liang-Hsiung; (Taipei
City, TW) ; Huang, Shih-Fang; (Pingtung City,
TW) |
Correspondence
Address: |
ROSENBERG, KLEIN & LEE
3458 ELLICOTT CENTER DRIVE-SUITE 101
ELLICOTT CITY
MD
21043
US
|
Family ID: |
34710782 |
Appl. No.: |
10/747282 |
Filed: |
December 30, 2003 |
Current U.S.
Class: |
600/509 |
Current CPC
Class: |
A61B 5/0245
20130101 |
Class at
Publication: |
600/509 |
International
Class: |
A61B 005/04 |
Claims
What is claimed is:
1. An analysis method about probing into relationship of a beating
signal and a heart function, used to deal with the beating signal
measured from a subject under any activity condition in a period of
time with an electric manometer, the analysis can be a reference
target of the heart function of the subject, the method comprises:
(1) transforming the beating signal into a power spectrum by
performing a power spectrum transformation; (2) normalizing the
power spectrum outputted by the power spectrum transformation; and
(3) computing a pre-defined heart index from the normalized power
spectrum, and supplying the reference target of the heart function
from the subject with the heart index.
2. The method of claim 1, before the step (1), further comprises a
step of omitting the beating signal in the period of time before
pump of the electric manometer stopped.
3. The method of claim 1, wherein the step (1) comprises: (1-1)
performing a frequency domain transformation of the beating signal
to obtain a corresponding spectrum; and (1-2) computing a power
spectrum density of the spectrum.
4. The method of claim 3, wherein the step (1-1) is performed with
fast Fourier transform (FFT).
5. The method of claim 1, wherein the step (2) comprises an energy
normalization step (2-1) and a frequency normalization step
(2-2).
6. The method of claim 5, wherein the energy normalization step
(2-1) utilizes amplitude of a maximum fundamental wave in the
energy spectrum to be a normalizing standard.
7. The method of claim 5, wherein the frequency normalization step
(2-2) utilizes a selected heartbeat to be a normalizing
standard.
8. The method of claim 1, before the step (3), further comprises a
step of defining the heart index, and the heart index is defined as
a sum of a meaningful spike counts in all intervals of the
normalized energy spectrum diagram.
9. The method of claim 8, wherein the meaningful spike is defined
by: if [S(i)-S(i-1)>V.sub.0 or S(i)-S(i-2)>V.sub.0]and
[S(i)-S(i+1)>V.sub.0 or S(i)-S(i+2)>V.sub.0]the i.sub.th
point is the meaningful spike, wherein S(i) is the normalized
energy spectrum of the i.sub.th point, V.sub.0=P.sub.1/N, P1 is the
amplitude of the maximum fundamental wave in the normalized energy
spectrum, and N is a constant.
10. The method of claim 9, wherein the constant N is 50.
11. A storage media stored a program that can execute the method of
claim 1.
12. An analysis method about probing into relationship of a beating
signal and a heart function, used to deal with the beating signal
measured from a subject under any activity condition in a period of
time with an electric manometer, the analysis can be a reference
target of the heart function of the subject, the method comprises:
(1) performing a frequency domain transformation of the beating
signal to obtain a corresponding spectrum; and (2) computing a
power spectrum density of the spectrum to obtain a corresponding
energy spectrum diagram.
13. The method of claim 12, before the step (1), further comprises
a step of omitting the beating signal in the period of time before
pump of the electric manometer stopped.
14. The method of claim 12, before the step (2), further comprises
a step (3) of normalizing the energy spectrum diagram.
15. The method of claim 14, after the step (3), further comprises a
step of computing a pre-defined heart index by the normalized
energy spectrum diagram.
16. A storage media stored a program that can execute the method of
claim 12.
17. A method for determining a heart function with a beating
signal, used to deal with the beating signal measured from a
subject under any activity condition in a period of time with an
electric manometer, the analysis can be a reference target of the
heart function of the subject, the method comprises: (1)
transforming the beating signal into a power spectrum by performing
a power spectrum transformation; (2) normalizing the power spectrum
outputted by the power spectrum transformation; (3) computing a
pre-defined heart index from the normalized power spectrum; and (4)
determining the heart function of the subject according to the
heart index.
18. The method of claim 17, wherein the step (4) includes
determining whether the subject has a heart disease.
19. The method of claim 17 or claim 18, wherein the step (4)
includes determining kind of the heart disease of the subject.
20. A storage media stored a program that can execute the method of
claim 17.
Description
BACKGROUND OF INVENTION
[0001] 1. Field of the Invention
[0002] The invention relates to an analysis method, and more
particularly, to an analysis method that utilizing the beating
signal measured under any activity condition with an electric
manometer to be a reference target for determining the relationship
of the beating signal and the heart function.
[0003] 2. Description of the Prior Art
[0004] The heart disease is always called "the invisible killer",
and when a patient is found having the heart disease, it is
generally the last phase and cannot be cured. In fact, for the
worldwide medical treatment, the initial and medium phases of the
heart disease are hard to be found, and this causes many cases of
dying in heart strike.
[0005] In comparison with the prophylaxis of the heart disease, the
manometer has become popular in every family with its cheap price,
and the prophylaxis of the high blood pressure can be easily
carried out. The electric manometer is the most popular one for
families or individuals with its simple operation. The electric
manometer not only can measure the systolic pressure and the
diastolic pressure but also can measure the pulse signal, such as
the pulse count, for user reference. However, the pulse signal is
one auxiliary function of the electric manometer, and is not paid
much attention.
SUMMARY OF INVENTION
[0006] It is therefore a primary objective of the claimed invention
to provide an analysis method utilizing the beating signal measured
with the electric manometer to be a reference target for
determining the relationship of the beating signal and the heart
function.
[0007] It is therefore another objective of the claimed invention
to provide an analysis method about probing into relationship of a
beating signal and a heart function that is suitable to a subject
under any activity condition.
[0008] The present invention discloses an analysis method about
probing into relationship of a beating signal and a heart function.
The method can be used to deal with the beating signal measured
from a subject under any activity condition in a period of time
with an electric manometer, and the analysis can be reference
target of the heart function of the subject. The method comprises:
(1) transforming the beating signal into a power spectrum by
performing a power spectrum transformation; (2) normalizing the
power spectrum outputted by the power spectrum transformation; and
(3) computing a pre-defined heart index from the normalized power
spectrum, and supplying the reference target of the heart function
from the subject with the heart index.
[0009] The present invention further discloses a method for
determining a heart function with a beating signal. The method
comprises: (1) transforming the beating signal of a subject into a
power spectrum by performing a power spectrum transformation; (2)
normalizing the power spectrum outputted by the power spectrum
transformation; (3) computing a pre-defined heart index from the
normalized power spectrum; and (4) determining the heart function
of the subject according to the heart index.
[0010] These and other objectives of the present invention will no
doubt become obvious to those of ordinary skill in the art after
reading the following detailed description of the preferred
embodiment that is illustrated in the various figures and
drawings.
BRIEF DESCRIPTION OF DRAWINGS
[0011] FIG. 1 is a flow chart of a preferred embodiment of an
analysis method for determining the relationship of the beating
signal and the heart function according to the present
invention.
[0012] FIG. 2 is a complete original signal chart obtained by the
step of beating measurement of the preferred embodiment.
[0013] FIGS. 3a and 3b are a measured backend beating signal chart
and an energy spectrum diagram of the backend beating signal after
the energy spectrum transformation.
[0014] FIG. 4a is a backend beating signal and an energy spectrum
diagram of a normal subject with heartbeat 80 times/min measured
under rest status, and FIG. 4b is a result of the FIG. 4a after
frequency normalization and energy normalization.
[0015] FIG. 5a is a backend beating signal and an energy spectrum
diagram of a normal subject with heartbeat 120 times/min measured
after exercising, and FIG. 5b is a result of the FIG. 5a after
frequency normalization and energy normalization.
[0016] FIG. 6a is a backend beating signal and an energy spectrum
diagram of a cardiomyopathy patient with heartbeat 65 times/min
measured under rest status, and FIG. 6b is a result of the FIG. 6a
after frequency normalization and energy normalization.
[0017] FIG. 7 is a schematic diagram of defining steps of a heart
index according to the preferred embodiment.
[0018] FIG. 8 is a captured signal and an energy spectrum analysis
diagram of a valvular heart disease patient's heartbeat.
[0019] FIG. 9 is a captured signal and an energy spectrum analysis
diagram of a cardiomyopathy patient's heartbeat.
[0020] FIG. 10 is a captured signal and an energy spectrum analysis
diagram of an arrhythmia patient's heartbeat.
[0021] FIG. 11 is a captured signal and an energy spectrum analysis
diagram of a coronary artery patient's heartbeat.
[0022] FIG. 12 is a captured signal and an energy spectrum analysis
diagram of a non-heart disease patient's heartbeat.
[0023] 11 step of beating measurement
[0024] 12 step of frontend signal removing
[0025] 13 step of frequency domain transformation
[0026] 14 step of energy spectrum transformation
[0027] 15 step of normalization
[0028] 151 step of energy normalization
[0029] 152 step of frequency normalization
[0030] 16 step of defining the heart index
[0031] 17 step of computing the heart index
[0032] 31 original signal
[0033] 311 frontend beating signal
[0034] 312 backend beating signal
DETAILED DESCRIPTION
[0035] A preferred embodiment of the present invention is described
below to explain the features and the advantages of the claimed
technology.
[0036] Please refer to FIG. 1, the preferred embodiment of the
claimed analysis method about probing into relationship of beating
signal and heart function includes: a step of beating measurement
11, a step of frontend signal removing 12, a step of frequency
domain transformation 13, a step of energy spectrum transformation
14, a step of normalization 15, a step of defining the heart index
16 and a step of computing the heart index 17.
[0037] In the step of beating measurement 11 of this embodiment, a
electric manometer, which can detect 16 beating signal in one
second, is used to measure the heartbeat of the subject. The
measured original signal is shown in FIG. 2, and the dotted line
means the pressure. The pressure belt of the manometer is pumped
and the pressure is raised in the beginning, and the motor of the
pump is stopped at the highest pressure and the pressure is
gradually decreased. The filled line means the measured beating
signal. The frontend beating signal 311 has more noise caused by
the pump operation, and after the pump stopped, the backend beating
signal is lowered and has regularity to analyze.
[0038] When the original time domain signal 31 transforms to the
frequency domain, the beating signal spectrum diagram can help to
understand and determine the signal feature and meaning. In this
embodiment, the frontend beating signal 311 is proceeded with the
step of frontend signal removing 12 (the reason id explained
below), and the step of frequency domain transformation 13 is
performed with the fast Fourier transform (FFT) calculation. The
calculation is shown in [equation 1], and other conventional
methods for transforming the time domain signal 31 to the frequency
domain are also suitable. 1 X ( n ) = k = 0 N - 1 x 0 ( k ) W N kn
[ equation 1 ]
[0039] [equation 1] 2 wherein , W N = - j 2 N
[0040] x.sub.0: the original time domain signal
[0041] X: the spectrum of transforming the original signal to the
frequency domain
[0042] N: the inputted signal count
[0043] j:{square root}-1
[0044] n=0, 1, . . . N-1
[0045] The length of the original signal x.sub.0 is varied
according to the pulse measuring time, and in this embodiment,
using the signal detected 16 times/min. The sequence x.sub.0 is
performed a 1024 points FFT to obtain the spectrum X of
transforming the original signal 31 to the frequency domain. After
the step of frequency domain transformation 13, since the noise
signal of the pump operation and the human beating signal are
overlapped in the frequency domain, the step of frontend signal
removing 12 should remove the frontend beating signal 311 before
the pump stopped and perform the frequency domain transformation
with the backend beating signal 312.
[0046] The step of energy spectrum transformation 14 is multiplying
the spectrum X of the backend beating signal 312 obtained by the
step of frequency domain transformation 13 with its conjugate value
conj (X), and the power spectrum density S of X is obtained. The
power spectrum density S means the energy distribution status of
signals in the frequency domain, and can be shown by [equation 2].
FIGS. 3a and 3b show a measured backend beating signal 312 and an
energy spectrum diagram of the backend beating signal 312 after
transformation of steps 13 and 14.
S=X*conj(X)/n [equation 2]
[0047] Wherein, n: length of X
[0048] For evaluating whether the beating signal is affected by
subject's status, a comparison research is made and found that
although the heartbeat is faster, the energy is larger, and the
blood pressure is varied after exercising, the signal features of
the heart index are still obvious to be normalized and the subject
doesn't need to rest a period of time. The present invention can be
applied to subjects in any status without affecting the result.
[0049] In this embodiment, the step of normalization 15 includes a
step of energy normalization 151 and a step of frequency
normalization 152. The step of energy normalization 151 is
selecting the amplitude of a maximum fundamental wave from the
power spectrum density diagram in FIG. 3b, and the corresponding
frequency is defined as the first main frequency which is generally
located at 1 Hz (in the figure, the signal of 0 Hz shows the
average value without zeroing and isn't related to vibration). The
other waves with smaller amplitudes are called harmonic waves, and
are defined as the second and third main frequencies. The amplitude
of the first main frequency is defined 100% (the energy normalizing
standard in this embodiment), and dividing the amplitudes of the
harmonic waves with the amplitude of the first main frequency to
clearly observe the amplitude proportion relationship of the energy
after normalizing.
[0050] The step of frequency normalization 152 is defining the
heartbeat 80 times/min, that is 1.33 time/sec, and an electric
manometer which can detect 16 beating signals in one second is used
to obtain 21.28 beating signals. The pulse count in one minute is
divided with the normalizing standard 80 and is multiplied with the
time sequence, and the beating status after frequency normalizing
is obtained.
[0051] FIGS. 4 to 6 show the result of the step of normalization
15. FIG. 4a includes a backend beating signal 312 of a normal
subject with heartbeat 80 times/min measured under rest status (the
upper diagram) and an energy spectrum diagram of the backend
beating signal 312 after normalizing with steps 13 and 14 (the
lower diagram) The amplitude of the first main frequency shown in
the energy spectrum diagram is about 2.8.times.10.sup.5. FIG. 4b is
a result of the FIG. 4a normalized the heartbeat as 80 times/min
and the amplitude of the first main frequency as
5.times.10.sup.5.
[0052] Similarly, FIG. 5a includes a backend beating signal 312 of
the same subject with heartbeat 120 times/min measured after
exercising (the upper diagram) and an energy spectrum diagram (the
lower diagram). The amplitude of the first main frequency shown in
the energy spectrum diagram is about 6.1.times.10.sup.5. FIG. 5b is
a result of the FIG. 5a normalized the heartbeat as 80 times/min
and the amplitude of the first main frequency as
5.times.10.sup.5.
[0053] FIG. 6a includes a backend beating signal 312 (the upper
diagram) and an energy spectrum diagram (the lower diagram) of a
cardiomyopathy patient with heartbeat 65 times/min measured under
rest status. The amplitude of the first main frequency shown in the
energy spectrum diagram is about 8.9.times.10.sup.5. FIG. 6b is a
result of the FIG. 6a normalized the heartbeat as 80 times/min and
the amplitude of the first main frequency as 5.times.10.sup.5. In
FIG. 6b, the main frequency position of the cardiomyopathy patient
is more difficult to identify than that of a normal person, and the
non-zero energy spectrums between each main frequencies are
frequently appeared.
[0054] After analyzing a large number of measured data, the beating
energy spectrum diagram of a non-heart disease person can be read
out 4 to 5 main energy distributions (the main frequencies)
according to the personal heartbeat speed. The biggest energy is
found near 1 Hz, and the energy decreases gradually forward to the
high frequency end. Besides the 4 or 5 main spectrums, no other
obvious spectrum distribution is found and the value on the
frequency axis is generally zero.
[0055] The beating energy spectrum diagram of a heart disease
patient can be also read out 4 to 5 main frequencies, but some
spectrums whose energy is smaller than that of the main frequency
are observed. Wider the non-zero spectrum distributing means more
irregular the captured beating signal is, and includes unstable
signals. Moreover, the worse one has much larger irregular signal
energy and cannot determine position of the main frequency. So, in
the energy spectrum diagram of a patient, besides the main
frequencies, the amount of the non-zero energies appeared on the
frequency domain is greatly related to whether the patient has a
heart disease.
[0056] With the step of defining the heart index 16 and the step of
computing the heart index 17, the determining criteria of the
relationship between the beating signal energy spectrum analysis
and the heart function can be quantified and formulated. The
claimed invention can be performed in a software program operated
with a storage media storing the software program (such as the
floppy disk, the optical disk or the hard disk) and an electric
device that can execute this software program (such as the
computer, the PDA or the clinical equipment) to rapidly compute and
provide the subject for reference.
[0057] In the step of defining the heart index 16, the heart index
is defined as follows. Firstly, in the energy spectrum diagram
obtained by the step 15, defining the 0 point to the first main
frequency as the first interval, the first to second main
frequencies as the second interval, the second to third main
frequencies as the third interval, and the third to fourth even
fifth main frequencies as the fourth interval. As shown in FIG. 7,
when the energy spectrum distribution status of the intervals
matches [equation 3], a meaningful spike at i point is defined.
if [S(i)-S(i-1)>V.sub.0 or S(i)-S(i-2)>V.sub.0]
and [S(i)-S(i+1)>V.sub.0 or S(i)-S(i+2)>V.sub.0] [equation
3]
[0058] Wherein, V.sub.0=P.sub.1/50, P.sub.1 is the amplitude of the
first main frequency. The heart index is defined as a sum of the
meaningful spike counts in the first to fourth intervals.
[0059] In the step of computing the heart index 17, the definition
of step 16 is used to compute the heart indexes of FIGS. 4b, 5b and
6b, and the heart indexes of FIGS. 4b and 5b are all 0. In other
words, although the normalized heartbeat and spectrum energy values
of same subject before and after exercising are different, the
heart indexes are the same and not affected by status of the
subject. In FIG. 6b, the heart index of a heart disease patient is
23 after normalizing, and is different to that in FIGS. 4b and 5b,
so the heart index can be a quantified and objective determining
criteria to determine the heart disease.
[0060] Please pay attention to that the heart index is not limited
by [equation 3], and the parameter V.sub.0 can be also adjusted.
The computing methods utilizing the variation of the strike or
other waves in the energy spectrum diagram to compute the heart
index are all claimed in the present invention.
[0061] The clinical observation and analysis result in one hospital
is disclosed below. The 201 subjects are diagnosed in the
department of cardiac medical, wherein the amount of the diagnosed
heart disease patients is 53 and the amount of the non-heart
disease patients is 148. With the heart index computing and the
clinical diagnosis, the heart index can be divided as follows to be
the reference for determining the heart function:
[0062] The heart index above 7: the abnormal beating frequency of
heart is frequent and obvious, and the cardiac muscle systole is
abnormal, and this is the feature of multiple heart diseases;
[0063] The heart index 4.about.6: The heart beats abnormal, and
this is the feature of the highly dangerous group of the heart
disease or already got a heart disease; and
[0064] The heart index below 3: The heart beating frequency is
normal, and the heart index of a healthy person is generally 0.
[0065] If analyzing the 53 diagnosed heart disease patients,
wherein amount of the valvular heart disease patient is 13, amount
of the cardiomyopathy patient (includes the cardiomyopathy and
myocarditis) is 12, amount of the arrhythmia patient is 7, and
amount of the coronary artery patient is 21. The related statistics
of the diseases and the heart index is shown in Table 1.
1TABLE 1 Related statistics of diseases and heart index Heart index
0.about.3 4.about.6 Above 7 Diseases (Percentage) (Percentage)
(Percentage) valvular 1 (7.69%) 1 (7.69%) 11 (84.62%) heart 12
(92.31%) disease cardiomyopathy 1 (8.33%) 3 (25.00%) 8 (66.67%)
disease 11 (91.67%) Arrhythmia 1 (14.29%) 4 (57.14%) 2 (28.57%)
disease 6 (85.71%) coronary 7 (33.33%) 6 (28.57%) 8 (38.10%) artery
14 (66.67%) disease sum 10* (18.87%) 14 (26.42%) 29 (54.72%) 43
(81.13%)
[0066] In Table 1, between all samples, the valvular heart disease
is 13. The abnormal status detecting rate is 84.62% and the
suspected abnormal status detecting rate is 7.69%, so the total
detecting rate is 92.31%. Between the 11 cardiomyopathy disease
samples, the abnormal status detecting rate is 66.67% and the
suspected abnormal status detecting rate is 25%, so the total
detecting rate is 91.67%. Between the 7 arrhythmia disease samples,
the abnormal status detecting rate is 28.57% and the suspected
abnormal status detecting rate is 57.14%, so the total detecting
rate is 85.71%. Between the 21 coronary artery disease samples, the
abnormal status detecting rate is 38.10% and the suspected abnormal
status detecting rate is 28.57%, so the total detecting rate is
66.67% and the missed rate is 33.33% which will be explained
below.
[0067] The amount of total samples is only 53. Since the body is
too small, the percentage is only for reference and cannot be a
conclusion.
[0068] The relationship and possible cause of the heart diseases
and the heart indexes are described below:
[0069] Firstly, the valvular heart disease can be sorted into the
aortic valve abnormality, the mitral valve abnormality, the
pulmonary valve abnormality, the tricuspid valve abnormality, and
the atrium or ventricle septal defect. Different reasons will lead
to different beating spectrum distribution. For example, if the
aortic valve is fibered by the congenital defect or calcification
and narrowed the aortic valve, the narrowed aortic valve will block
the blood of left ventricle into the aortic while the heart
systole, and the narrowed degree will lead to different
consequences. At this moment, the heart will try to compensate the
imbalance situation of the blood circulation (the compensation
effect), and prevent the blood flowed from the left ventricle to
the aorta few. There are some emergency measures of the heart:
[0070] 1. strengthening the systolic power of the left ventricle,
and this will cause the left ventricular hypertrophy to push the
blood; and
[0071] 2. extending the systole time, and more blood will flow from
the left ventricle into the aorta when the systole time is
extended.
[0072] The above-mentioned methods will increase workload and
strengthen blood pressure of the left ventricle. The heart works
powerfully and rapidly, but the pulse is still weak and the patient
feels tired, hard breathed, dizzy or chest pain. As show in FIG. 8,
which shows a captured signal and an energy spectrum analysis
diagram of a valvular heart disease patient's heartbeat. In the
energy spectrum diagram, when flowing from the left ventricle into
the aorta, the blood is blocked and has an extra abnormal signal.
In addition, when the systole time is increased or the power is
changed, the analysis can also show the difference, and the heart
index is 22.
[0073] FIG. 9 is a captured signal and an energy spectrum analysis
diagram of a cardiomyopathy patient's heartbeat, and the heart
index is 22.
[0074] FIG. 10 is a captured signal and an energy spectrum analysis
diagram of an arrhythmia patient's heartbeat, and the heart index
is 5. In the diagrams of the arrhythmia patients, the heart indexes
are generally 4 to 6 with percentage 57%, and the heart index
greater than 7 is 28.57%. Although the arrhythmia can be detected
with the claimed method, the energy spectrum diagram has only few
extra frequency distributions, and unlike that of the valvular
heart disease or cardiomyopathy patients having obvious features
with above 10 or 20 heart index. In the diagrams of the arrhythmia
patients, although the missing percentage is 14.29%, the value has
no statistics meaning with few samples. The missing case is a 75
years old man, whose signal is particularly weak and cannot find
the abnormality.
[0075] FIG. 11 is a captured signal and an energy spectrum analysis
diagram of a coronary artery patient's heartbeat, and the heart
index is 5. The block in the coronary artery is generally caused by
the atherosclerosis. The cholesterol and lipoids are coated inside
the artery, and the coronary artery diseases also include the
congenital defect or the coronary artery abnormally dilation. When
the coronary artery has pathological changes and cannot supply
heart muscle oxygen and nutrition, the ischemic heart disease is
happened. The ischemic heart disease cannot be observed while
resting, but when the workload of heart is increased (such as
exercising, weather changed or the mood emoted), the patient will
have angina pectoris for lacking oxygen.
[0076] In cases of the coronary artery disease, the detecting
percentage is 38.1%, the suspected abnormal percentage is 28.57%,
and the missing percentage is 33.33%. This result means that during
the coronary artery patients, about 60% will have the abnormal
systole frequency of the heart muscle, and above 30% cannot be
found while resting.
[0077] Among the above-mentioned 148 non-heart disease subjects,
the hypertension patients is the most with 110 cases, and the
related statistics of the heart index of the hypertension and
non-hypertension patients is shown in Table 2.
2TABLE 2 Related statistics of the heart index of the hypertension
and non-hypertension patients Heart index 0.about.3 4.about.6 Above
7 Diseases (percentage) (percentage) (percentage) hypertension 70
(63.64%) 26 (23.64%) 14 (12.73%) 40 (36.36%) non-hypertension 31
(81.58%) 5 (13.16%) 2 (5.26%) non-heart 7 (18.42%) disease sum 101
(68.24%) 31 (20.95%) 16 (10.81%) 47 (31.76%)**
[0078] In Table 2, the percentage of the hypertension group whose
heart index greater than 4 is 36.37%, that is higher than that of
the non-hypertension group, 18.42%. In other words, the abnormal or
suspected abnormal percentage of the myocardium systole frequency
of the hypertension patient is high than that of the normal people.
In fact, the hypertension group is the highly dangerous group of
getting the heart disease, and some of them already have the
symptom. FIG. 12 is a captured signal and an energy spectrum
analysis diagram of a non-heart disease patient's heartbeat, and
the heart index is 0. The frequency distribution is regularly and
clearly different from that of FIGS. 8 to 11.
[0079] In contrast to the prior art, the present invention has
these advantages:
[0080] 1. The present invention only utilizes the electric
manometer to measure the beating signal and be the reference of the
heart function without other extra or expansive detecting
equipments, so the claimed method is a cheap, safe, simple and
popular one that can be popularized to every families. The users
can determine the heart function when measuring the blood pressure
to be the reference of health care.
[0081] 2. With the difference of the beating energy spectrum
diagram between FIGS. 4a, 5a and 6a, position of the main
frequencies of the cardiomyopathy patient is difficult to identify
than that of a normal person. The non-zero energy spectrum is
frequently appeared between each main frequency, so the beating
energy spectrum diagram can be a reference to determine whether the
subject has a heart disease.
[0082] 3. With normalizing the energy spectrum, features of the
heart index are all similar under resting or exercising status. The
present invention can be used under any status, time or place, and
has much flexibility than other detecting methods.
[0083] 4. As described above, the present invention utilizes a
software program and a computer to rapidly compute. The subject can
immediately get the result and can prevent as soon as possible, and
the doctor can also take a suitable treat as soon as possible.
[0084] 5. In the actual application, the detected percentage of the
heart disease with the present invention depends on kinds of the
heart diseases, and not every kind of heart disease can lead to the
myocardium systole or beating frequency abnormality. The average
detected percentage of the mentioned samples is about 80%, and can
prove the practicability and reliability.
[0085] 6. In the mentioned samples, people diagnosed as normal by
the doctor still have about 32% suspected (especially the
hypertension patients) so the detecting standard of the heart
disease of the present invention is strict than that of doctors,
and can warn the patients in advance.
[0086] Those skilled in the art will readily observe that numerous
modifications and alterations of the device may be made while
retaining the teachings of the invention. Accordingly, the above
disclosure should be construed as limited only by the metes and
bounds of the appended claims.
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